Location-Aware Climate Control for Data Center Hotspot Mitigation
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Solution Overview
Problem
Existing climate control systems in data centers struggle to efficiently address localized temperature variations, such as hotspots, leading to energy inefficiency and undercooling of other areas, as they often operate all units simultaneously, which is costly and wasteful.
Innovation Solution
A location-aware climate control system with distributed climate sensors and control units that determine load-specific impact data to identify and target specific climate control units for localized adjustments, such as increasing fan speed or adjusting temperature settings, to mitigate anomalies like hotspots.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If all climate control units are activated simultaneously to address a hotspot, then the hotspot is mitigated, but other portions of the data center are undercooled resulting in substantial energy usage
Solution Approach 1:
The system determines relative impact data for each climate control unit on specific loads and selectively activates only those units with the greatest impact on the identified hotspot. This localized approach ensures cooling capacity is applied precisely where needed rather than uniformly across all units, preventing undercooling of other areas and reducing overall energy consumption.
Solution Approach 2:
The climate control system segments the response to hotspots by identifying and activating specific subsets of climate control units based on their relative impact on different loads. Instead of treating all units uniformly, the system divides them into groups based on their spatial and functional impact, allowing targeted activation of only the necessary units to address each hotspot location.
2Stability of the object's composition
If multiple climate control units operate together in teamwork mode, then conflicting operations are prevented, but the system cannot mitigate localized hotspots efficiently
Solution Approach 1:
The system dynamically adjusts the operational mode of climate control units based on real-time conditions. Rather than maintaining a fixed teamwork mode for all operations, the system transitions between coordinated operation and independent targeted activation depending on whether the situation requires global stability or localized hotspot mitigation, optimizing both coordination and efficiency.
Solution Approach 2:
The system changes operational parameters by determining relative impact data for each climate control unit on specific loads. This parameter-based approach allows the system to selectively activate units with the greatest impact on hotspots while maintaining coordinated operation for other functions, thereby improving hotspot mitigation efficiency without sacrificing operational stability.
3Temperature
If climate control units are distributed throughout the data center, then localized temperature regulation is improved, but the complexity of determining which units to activate increases
Solution Approach 1:
Each climate control unit determines its own relative impact data on nearby loads based on its location and operational characteristics. This self-service approach allows distributed units to autonomously assess their relevance to hotspots without requiring complex centralized calculations for each unit, simplifying the overall control system while maintaining effective localized temperature regulation.
Solution Approach 2:
The system uses climate sensors to provide real-time feedback on temperature conditions and activates climate control units based on this feedback and their determined relative impact data. This feedback mechanism simplifies control by automatically responding to measured conditions rather than requiring complex predictive modeling, enabling effective distributed temperature regulation with manageable system complexity.
Data Source
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AI summary
A climate control system may include climate sensors distributed within an environment containing a plurality of loads as well as control units distributed within the environment. The system may include a controller communicatively coupled with the climate sensors and the climate control units. The controller may receive localized climate data from the climate sensors. The controller may determine, for each of the climate control units, load-specific impact data associated with at least one incremental change of one or more operational settings on the loads based on the localized climate data. The controller may identify a localized climate anomaly based on the localized climate data. The controller may provide, in response to the localized climate anomaly, a targeted climate adjustment of at least one of the one or more operational settings of a subset of the climate control units based on the load-specific impact data.